A simple and efficient method for breast cancer diagnosis based on infrared thermal imaging.

This study aims to evaluate the feasibility and efficacy of quantitative diagnosis through thermal analysis of abnormal metabolism. In this paper, an analytical-based steady-state solution for the thermal inverse problem was developed, considering an equivalent point heat source embedded in the tissue. Based on this solution, we developed a simple and efficient algorithm that generates solutions for the nonlinear heat conduction model. Using the nonlinear fitting analysis, a regular distribution can be derived from the raw thermal patterns of the skin surface above the tumor, and the power and depth of the equivalent heat source can be derived to investigate whether the tumor is malignant or benign. The thermal power Q of internal heat source was estimated to predict the satisfactory approaches to distinguish between benign and malignant tumors. The results of four clinical cases (female patients with malignant tumor and benign tumor) show that the estimated values of the power of the heat sources in malignant cases (fatty: Q = 0.34851 W; dense: Q = 0.46933 W) are both far greater than the ones in benign (fatty: Q = 0.04721 W; dense: Q = 0.07717 W), irregardless of the breast density. The correlation coefficients (R (2)) of the nonlinear curve fittings are all above 0.98. The new thermal method proposed in this study would help to improve the preciseness of diagnosis on breast masses (malignant or benign).